These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.
    Author: Sovány T, Papós K, Kása P, Ilič I, Srčič S, Pintye-Hódi K.
    Journal: AAPS PharmSciTech; 2013 Jun; 14(2):511-6. PubMed ID: 23413109.
    Abstract:
    The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.
    [Abstract] [Full Text] [Related] [New Search]